-----------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\jdr08_000\Documents\Information_And_Economic_Voting.log
  log type:  text
 opened on:  10 May 2016, 14:47:01

. 
. ************
. * Figure 1 *
. ************
. 
. clear

. set more off

. 
. ** For Politicians:
. use all_sessions_full, clear

. keep if type>0
(3840 observations deleted)

. 
. gen Incumbent = 1 if type==current_incumbent
(256 missing values generated)

. replace Incumbent = 0 if type!=current_incumbent
(256 real changes made)

. 
. label define Incumbent 1 "Incumbent"

. label define Incumbent 0 "Candidate", add

. label values Incumbent Incumbent

. 
. ** Final allocations
. gen final_1 =  endowment_1+ delta_welfare_1

. gen final_2 =  endowment_2+ delta_welfare_2

. gen final_3 =  endowment_3+ delta_welfare_3

. 
. gen s = final_1+final_2+final_3

. gen f1 = final_1/s

. gen f2 = final_2/s

. gen f3 = final_3/s

. 
. triplot f1 f2 f3 if treatment==1 , ltext(Community 1) rtext(Community 2) btext(Community 3) separat
> e(Incumbent) y label(nolabels) bltext(100% C3) brtext(100% C2) ttext(100% C1) text(mlabsize(large))

. graph export "`graphs_dir'triplot_A_bw.eps", as(eps) preview(off) replace 
(file triplot_A_bw.eps written in EPS format)

. triplot f1 f2 f3 if treatment==2 , ltext(Community 1) rtext(Community 2) btext(Community 3) separat
> e(Incumbent) y label(nolabels) bltext(100% C3) brtext(100% C2) ttext(100% C1) text(mlabsize(large))

. graph export "`graphs_dir'triplot_B_bw.eps", as(eps) preview(off) replace
(file triplot_B_bw.eps written in EPS format)

. triplot f1 f2 f3 if treatment==3 , ltext(Community 1) rtext(Community 2) btext(Community 3) separat
> e(Incumbent) y label(nolabels) bltext(100% C3) brtext(100% C2) ttext(100% C1) text(mlabsize(large))

. graph export "`graphs_dir'triplot_C_bw.eps", as(eps) preview(off) replace
(file triplot_C_bw.eps written in EPS format)

. triplot f1 f2 f3 if treatment==4 , ltext(Community 1) rtext(Community 2) btext(Community 3) separat
> e(Incumbent) y label(nolabels) bltext(100% C3) brtext(100% C2) ttext(100% C1) text(mlabsize(large))

. graph export "`graphs_dir'triplot_D_bw.eps", as(eps) preview(off) replace
(file triplot_D_bw.eps written in EPS format)

. 
. ** Summary:
. latabstat tax_rate final_1-final_3 if treatment==1, by (Incumbent) format(%9.2f) nototal

\begin{table}[htbp]\centering
\caption{\label{} 
\textbf{} }\begin{tabular} {@{} l r r r r @{}} \\ \hline
\textbf{Incumbent } & \textbf{  tax_rate} & \textbf{   final_1} & \textbf{   final_2} & \textbf{   fi
> nal_3} \\
\hline
Candidate  &      21.72 &    1340.38 &    1340.88 &    1352.20 \\
Incumbent  &      23.75 &    1305.20 &    1363.39 &    1355.72 \\
\hline
\multicolumn{5}{@{}l}{
\footnotesize{\emph{Source:} all_sessions_full.dta}}
\end{tabular}
\end{table}

. latabstat tax_rate final_1-final_3 if treatment==2, by (Incumbent) format(%9.2f) nototal

\begin{table}[htbp]\centering
\caption{\label{} 
\textbf{} }\begin{tabular} {@{} l r r r r @{}} \\ \hline
\textbf{Incumbent } & \textbf{  tax_rate} & \textbf{   final_1} & \textbf{   final_2} & \textbf{   fi
> nal_3} \\
\hline
Candidate  &      30.31 &    1913.33 &    1003.74 &    1002.43 \\
Incumbent  &      27.19 &    1966.43 &     985.20 &    1005.65 \\
\hline
\multicolumn{5}{@{}l}{
\footnotesize{\emph{Source:} all_sessions_full.dta}}
\end{tabular}
\end{table}

. latabstat tax_rate final_1-final_3 if treatment==3, by (Incumbent) format(%9.2f) nototal

\begin{table}[htbp]\centering
\caption{\label{} 
\textbf{} }\begin{tabular} {@{} l r r r r @{}} \\ \hline
\textbf{Incumbent } & \textbf{  tax_rate} & \textbf{   final_1} & \textbf{   final_2} & \textbf{   fi
> nal_3} \\
\hline
Candidate  &      27.81 &     896.56 &     923.75 &     910.06 \\
Incumbent  &      24.38 &     887.28 &     940.45 &     934.70 \\
\hline
\multicolumn{5}{@{}l}{
\footnotesize{\emph{Source:} all_sessions_full.dta}}
\end{tabular}
\end{table}

. latabstat tax_rate final_1-final_3 if treatment==4, by (Incumbent) format(%9.2f) nototal

\begin{table}[htbp]\centering
\caption{\label{} 
\textbf{} }\begin{tabular} {@{} l r r r r @{}} \\ \hline
\textbf{Incumbent } & \textbf{  tax_rate} & \textbf{   final_1} & \textbf{   final_2} & \textbf{   fi
> nal_3} \\
\hline
Candidate  &      23.59 &    1659.59 &    1327.13 &     985.80 \\
Incumbent  &      22.97 &    1650.69 &    1336.47 &    1021.92 \\
\hline
\multicolumn{5}{@{}l}{
\footnotesize{\emph{Source:} all_sessions_full.dta}}
\end{tabular}
\end{table}

. latabstat tax_rate final_1-final_3, by (Incumbent) format(%9.2f) nototal

\begin{table}[htbp]\centering
\caption{\label{} 
\textbf{} }\begin{tabular} {@{} l r r r r @{}} \\ \hline
\textbf{Incumbent } & \textbf{  tax_rate} & \textbf{   final_1} & \textbf{   final_2} & \textbf{   fi
> nal_3} \\
\hline
Candidate  &      25.86 &    1452.47 &    1148.87 &    1062.62 \\
Incumbent  &      24.57 &    1452.40 &    1156.38 &    1079.50 \\
\hline
\multicolumn{5}{@{}l}{
\footnotesize{\emph{Source:} all_sessions_full.dta}}
\end{tabular}
\end{table}

. 
. ***************
. ** Figure 2  **
. ***************
. 
. * The first three graphs are the panels individually.  The fourth is Figure 2, as presented in the 
> manuscript
. 
. ** For Voters:
. use all_sessions_full, clear

. keep if type==0
(512 observations deleted)

. 
. set scheme  s1manual 

. 
. twoway (lowess  total_info Period if treat==1, color(black)) (lowess  total_info Period if treat==2
> , color(gray)) (lowess  total_info Period if treat==3, color(black) lpattern(--)) (lowess  total_in
> fo Period if treat==4, color(gray) lpattern(--)),  legend(label(1 "Baseline") label(2 "Clustered") 
> label(3 "Poor") label(4 "Heterogeneous"))  ytitle(Fraction of Total Information)

. graph export "`graphs_dir'info_demand_per_period_total_bw.eps", as(eps) preview(off) replace
(file info_demand_per_period_total_bw.eps written in EPS format)

. 
. twoway (lowess  total_info Period if treat==1 & endowment==100, color(black)) (lowess  total_info P
> eriod if treat==2 & endowment==100, color(gray)) (lowess  total_info Period if treat==3 & endowment
> ==100, color(black) lpattern(--)) (lowess  total_info Period if treat==4 & endowment==100, color(gr
> ay) lpattern(--)),  legend(label(1 "Baseline") label(2 "Clustered") label(3 "Poor") label(4 "Hetero
> geneous"))  ytitle(Fraction of Total Information)

. graph export "`graphs_dir'info_demand_per_period_low_bw.eps", as(eps) preview(off) replace
(file info_demand_per_period_low_bw.eps written in EPS format)

. 
. twoway (lowess  total_info Period if treat==1 & endowment==500, color(black)) (lowess  total_info P
> eriod if treat==2 & endowment==500, color(gray)) (lowess  total_info Period if treat==3 & endowment
> ==500, color(black) lpattern(--)) (lowess  total_info Period if treat==4 & endowment==500, color(gr
> ay) lpattern(--)),  legend(label(1 "Baseline") label(2 "Clustered") label(3 "Poor") label(4 "Hetero
> geneous"))  ytitle(Fraction of Total Information)

. graph export "`graphs_dir'info_demand_per_period_high_bw.eps", as(eps) preview(off) replace
(file info_demand_per_period_high_bw.eps written in EPS format)

. 
. twoway (lowess  total_info Period if treat==1, color(black)) (lowess  total_info Period if treat==2
> , color(gray)) (lowess  total_info Period if treat==3, color(black) lpattern(--)) (lowess  total_in
> fo Period if treat==4, color(gray) lpattern(--)),  legend(label(1 "Baseline") label(2 "Clustered") 
> label(3 "Poor") label(4 "Heterogeneous")) by(endowment, total note("")) ytitle(Percentage of Total 
> Information)

. graph export "`graphs_dir'info_demand_per_period_bw.eps", as(eps) preview(off) replace
(file info_demand_per_period_bw.eps written in EPS format)

. 
. **************
. ** Figure 3 **
. **************
. 
. use all_sessions_full, clear

. keep if type==0
(512 observations deleted)

. 
. gen conflict=1  if IncumbentAdvantage<0 &  dist_tax>0
(3705 missing values generated)

. replace conflict=2 if IncumbentAdvantage>0 &  dist_tax<0
(1390 real changes made)

. replace conflict=3 if IncumbentAdvantage<0 &  dist_tax<0
(1320 real changes made)

. replace conflict=4 if IncumbentAdvantage>0 &  dist_tax>0
(135 real changes made)

. 
. label define conflict 1 "Negative Own vs. Positive National"

. label define conflict 2 "Positive Own vs. Negative National", add

. label define conflict 3 "Negative Own and Negative National", add

. label define conflict 4 "Positive Own and Positive National", add

. label values conflict conflict

. 
. gen election_app = -election

. 
. label define election_app -1 "Voting"

. label define election_app 0 "Approval", add

. label values election_app election_app

. 
. gen vote_approve = .
(3840 missing values generated)

. replace vote_approve = VoteIncumbent if election==1
(1200 real changes made)

. replace vote_approve = approve if election == 0
(2640 real changes made)

. 
. graph bar (mean) vote_approve if conflict==1, over(info_nat) by(election_app, note("")) ytitle(Prob
> ability of Voting for the Incumbent)  yscale(range(0 1))

. graph export "`graphs_dir'conflicts_Neg_Own_Pos_Nat_bw.eps", as(eps) preview(off) replace
(file conflicts_Neg_Own_Pos_Nat_bw.eps written in EPS format)

. 
. graph bar (mean) vote_approve if conflict==2, over(info_nat) by(election_app, note("")) ytitle(Prob
> ability of Voting for the Incumbent)  yscale(range(0 1))

. graph export "`graphs_dir'conflicts_Pos_Own_Neg_Nat_bw.eps", as(eps) preview(off) replace
(file conflicts_Pos_Own_Neg_Nat_bw.eps written in EPS format)

. 
. 
. ***********
. * Table 3 *
. ***********
. 
. use all_sessions_full, clear

. keep if type == 0
(512 observations deleted)

. 
. summarize tax_rate_inc if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_inc |       960       23.75    8.201071          0         40

. summarize tax_rate_cand if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_c~d |       960    21.71875    7.410506          0         40

. 
. summarize tax_rate_inc if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_inc |       960     27.1875    14.20123         10         70

. summarize tax_rate_cand if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_c~d |       960     30.3125     15.6175         10         70

. 
. summarize tax_rate_inc if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_inc |       960      24.375    12.23787          0         50

. summarize tax_rate_cand if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_c~d |       960     27.8125    15.05659          0         70

. 
. summarize tax_rate_inc if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_inc |       960    22.96875    10.56481         10         70

. summarize tax_rate_cand if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_c~d |       960    23.59375    14.19004          0        100

. 
. summarize tax_rate_inc

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_inc |      3840    24.57031    11.61924          0         70

. summarize tax_rate_cand

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
tax_rate_c~d |      3840    25.85938    13.89467          0        100

. 
. ***********
. * Table 4 *
. ***********
. 
. *Baseline Total
. summarize info_1_own if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       960    .2354167    .4244801          0          1

. gen avothers = (info_2_other_1 + info_3_other_2)/2

. summarize avothers if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       960    .1526042    .3483815          0          1

. summarize info_4_nation if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       960    .1791667    .3836917          0          1

. summarize info_5_tax if treatment == 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       960    .2739583    .4462203          0          1

. 
. *Baseline Low Endowment
. summarize info_1_own if treatment == 1 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       576    .2170139    .4125704          0          1

. summarize avothers if treatment == 1 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       576    .1432292    .3373389          0          1

. summarize info_4_nation if treatment == 1 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       576    .1736111     .379104          0          1

. summarize info_5_tax if treatment == 1 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       576    .2465278     .431364          0          1

. 
. *Baseline High Endowment
. summarize info_1_own if treatment == 1 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       384    .2630208     .440848          0          1

. summarize avothers if treatment == 1 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       384    .1666667    .3643132          0          1

. summarize info_4_nation if treatment == 1 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       384       .1875    .3908216          0          1

. summarize info_5_tax if treatment == 1 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       384    .3151042    .4651634          0          1

. 
. *Clustered Total
. summarize info_1_own if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       960    .2072917    .4055776          0          1

. summarize avothers if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       960    .1479167     .320479          0          1

. summarize info_4_nation if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       960    .1666667    .3728723          0          1

. summarize info_5_tax if treatment == 2

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       960     .303125    .4598484          0          1

. 
. *Clustered Low Endowment
. summarize info_1_own if treatment == 2 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       576    .1805556    .3849838          0          1

. summarize avothers if treatment == 2 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       576    .1380208    .2971673          0          1

. summarize info_4_nation if treatment == 2 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       576    .1527778    .3600859          0          1

. summarize info_5_tax if treatment == 2 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       576    .2708333    .4447764          0          1

. 
. *Clustered High Endowment
. summarize info_1_own if treatment == 2 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       384    .2473958    .4320617          0          1

. summarize avothers if treatment == 2 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       384    .1627604    .3524531          0          1

. summarize info_4_nation if treatment == 2 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       384       .1875    .3908216          0          1

. summarize info_5_tax if treatment == 2 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       384    .3515625    .4780811          0          1

. 
. 
. *Poor Total
. summarize info_1_own if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       960    .2458333    .4308046          0          1

. summarize avothers if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       960    .1177083    .3066842          0          1

. summarize info_4_nation if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       960    .1270833    .3332399          0          1

. summarize info_5_tax if treatment == 3

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       960    .2989583    .4580402          0          1

. 
. *Poor Low Endowment
. summarize info_1_own if treatment == 3 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       768    .2942708    .4560113          0          1

. summarize avothers if treatment == 3 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       768    .1425781     .333168          0          1

. summarize info_4_nation if treatment == 3 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       768    .1497396    .3570485          0          1

. summarize info_5_tax if treatment == 3 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       768    .3203125    .4669007          0          1

. 
. *Poor High Endowment
. summarize info_1_own if treatment == 3 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       192    .0520833     .222776          0          1

. summarize avothers if treatment == 3 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       192    .0182292    .1185912          0          1

. summarize info_4_nation if treatment == 3 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       192    .0364583    .1879177          0          1

. summarize info_5_tax if treatment == 3 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       192    .2135417    .4108782          0          1

. 
. 
. *Heterodox Total
. summarize info_1_own if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       960    .1322917    .3389842          0          1

. summarize avothers if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       960    .0604167    .2201901          0          1

. summarize info_4_nation if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       960      .10625    .3083179          0          1

. summarize info_5_tax if treatment == 4

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       960    .2041667    .4033015          0          1

. 
. *Heterodox Low Endowment
. summarize info_1_own if treatment == 4 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       576    .1336806    .3406046          0          1

. summarize avothers if treatment == 4 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       576    .0633681     .230074          0          1

. summarize info_4_nation if treatment == 4 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       576    .0989583    .2988656          0          1

. summarize info_5_tax if treatment == 4 & endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       576    .2065972    .4052158          0          1

. 
. *Heterodox High Endowment
. summarize info_1_own if treatment == 4 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |       384    .1302083    .3369716          0          1

. summarize avothers if treatment == 4 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |       384    .0559896    .2046855          0          1

. summarize info_4_nation if treatment == 4 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |       384    .1171875    .3220632          0          1

. summarize info_5_tax if treatment == 4 & endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |       384    .2005208    .4009125          0          1

. 
. 
. *Total Total
. summarize info_1_own

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |      3840    .2052083    .4039064          0          1

. summarize avothers

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |      3840    .1196615    .3048473          0          1

. summarize info_4_nation

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |      3840    .1447917    .3519365          0          1

. summarize info_5_tax

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |      3840    .2700521    .4440443          0          1

. 
. *Total Low Endowment
. summarize info_1_own if endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |      2496     .213141    .4096085          0          1

. summarize avothers if endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |      2496    .1233974    .3065704          0          1

. summarize info_4_nation if endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |      2496    .1442308     .351394          0          1

. summarize info_5_tax if endowment == 100

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |      2496     .265625    .4417539          0          1

. 
. *Total High Endowment
. summarize info_1_own if endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_1_own |      1344    .1904762    .3928229          0          1

. summarize avothers if endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
    avothers |      1344    .1127232     .301612          0          1

. summarize info_4_nation if endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
info_4_nat~n |      1344    .1458333    .3530704          0          1

. summarize info_5_tax if endowment == 500

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  info_5_tax |      1344    .2782738    .4483158          0          1

. 
. 
. ******************
. * Tables 5 and 6 *
. ******************
. 
. use all_sessions_full, clear

. 
. keep if type==0
(512 observations deleted)

. xtset Id Period
       panel variable:  Id (strongly balanced)
        time variable:  Period, 1 to 16
                delta:  1 unit

. 
. gen self =  sign(delta_own_welfare_1-delta_own_welfare_2) if current_incumbent==1
(1680 missing values generated)

. replace self =  sign(delta_own_welfare_2-delta_own_welfare_1) if current_incumbent==2
(1680 real changes made)

. 
. gen self_x_own = self*info_1

. gen self_x_others = self*info_others

. gen self_x_national = self*info_nat

. 
. gen own_comm =  sign(avg_delta_welfare_own_communi71- avg_delta_welfare_own_communi72) if current_i
> ncumbent==1
(1680 missing values generated)

. replace own_comm =  sign(avg_delta_welfare_own_communi72- avg_delta_welfare_own_communi71) if curre
> nt_incumbent==2
(1680 real changes made)

. 
. gen own_comm_x_own = own_comm*info_1

. 
. gen national =  sign(avg_delta_welfare_nation_1-avg_delta_welfare_nation_2) if current_incumbent==1
(1680 missing values generated)

. replace national =  sign(avg_delta_welfare_nation_2-avg_delta_welfare_nation_1) if current_incumben
> t==2
(1680 real changes made)

. 
. gen national_x_national = national*info_nat

. 
. gen fair = -sign(fair_inc-fair_cand)

. gen fair_x_others = fair*info_others

. 
. xi: xtprobit VoteInc self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==1
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -828.24649  
Iteration 1:   log likelihood = -569.21933  
Iteration 2:   log likelihood = -567.44981  
Iteration 3:   log likelihood = -567.44518  
Iteration 4:   log likelihood = -567.44518  

Fitting full model:

rho =  0.0     log likelihood = -567.44518
rho =  0.1     log likelihood = -571.36131

Iteration 0:   log likelihood = -571.36131  
Iteration 1:   log likelihood =  -568.1847  
Iteration 2:   log likelihood = -567.64419  
Iteration 3:   log likelihood = -567.48716  
Iteration 4:   log likelihood = -567.45135  
Iteration 5:   log likelihood =  -567.4465  
Iteration 6:   log likelihood = -567.44547  
Iteration 7:   log likelihood = -567.44525  
Iteration 8:   log likelihood = -567.44523  
Iteration 9:   log likelihood = -567.44522  

Random-effects probit regression                Number of obs      =      1200
Group variable: Id                              Number of groups   =       240

Random effects u_i ~ Gaussian                   Obs per group: min =         5
                                                               avg =       5.0
                                                               max =         5

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    427.78
Log likelihood  = -567.44522                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
      VoteIncumbent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |   1.029427   .0591219    17.41   0.000     .9135507    1.145304
         self_x_own |  -.3736703   .1533682    -2.44   0.015    -.6742665   -.0730741
      self_x_others |  -.0453858   .1617067    -0.28   0.779    -.3623252    .2715535
    self_x_national |  -.1527987   .1172623    -1.30   0.193    -.3826285    .0770312
     own_comm_x_own |   .4230149    .109188     3.87   0.000     .2090103    .6370195
      fair_x_others |  -.5131782    .121794    -4.21   0.000    -.7518901   -.2744663
national_x_national |    .069792   .1068749     0.65   0.514     -.139679    .2792629
        _Isession_2 |   .0896018    .246622     0.36   0.716    -.3937685    .5729721
        _Isession_3 |  -.0304106   .2439134    -0.12   0.901    -.5084721    .4476509
        _Isession_4 |   .3379433   .2407066     1.40   0.160     -.133833    .8097195
        _Isession_5 |  -.1588467   .2402552    -0.66   0.509    -.6297383    .3120448
        _Isession_6 |    -.05673   .2451768    -0.23   0.817    -.5372676    .4238076
        _Isession_7 |  -.2880086   .2401146    -1.20   0.230    -.7586246    .1826074
        _Isession_8 |  -.1278406   .2326864    -0.55   0.583    -.5838976    .3282165
        _Isession_9 |   .2629808   .2310072     1.14   0.255    -.1897851    .7157466
       _Isession_10 |  -.1872441   .2427082    -0.77   0.440    -.6629433    .2884552
       _Isession_11 |   .0513193   .2458252     0.21   0.835    -.4304893    .5331278
       _Isession_12 |  -.2736649   .2428932    -1.13   0.260    -.7497268     .202397
       _Isession_13 |  -.3026993   .2350299    -1.29   0.198    -.7633496    .1579509
       _Isession_14 |   .0905012   .2459816     0.37   0.713    -.3916138    .5726162
       _Isession_15 |   .3295744   .2452684     1.34   0.179    -.1511428    .8102916
       _Isession_16 |   .1955698   .2470901     0.79   0.429    -.2887179    .6798574
              _cons |   .1267558   .1703468     0.74   0.457    -.2071177    .4606292
--------------------+----------------------------------------------------------------
           /lnsig2u |  -12.58849   21.16965                     -54.08025    28.90327
--------------------+----------------------------------------------------------------
            sigma_u |   .0018469   .0195492                      1.81e-12     1889145
                rho |   3.41e-06   .0000722                      3.26e-24           1
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =  8.1e-05 Prob >= chibar2 = 0.496

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(VoteIncumbent=1 assuming u_i=0) (predict, pu0)
         =  .55043314
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .4073961        .025   16.30   0.000     .3584  .456392         0
self_x~n |  -.1478801      .06082   -2.43   0.015   -.26709  -.02867         0
self_x~s |  -.0179615      .06401   -0.28   0.779  -.143423    .1075         0
self_x~l |  -.0604701      .04638   -1.30   0.192  -.151364  .030424         0
own_co~n |   .1674083      .04323    3.87   0.000   .082671  .252146         0
fair_x~s |  -.2030904      .04819   -4.21   0.000  -.297533 -.108648         0
n~_x_n~l |   .0276202      .04227    0.65   0.514  -.055234  .110475         0
_Ises~_2*|   .0352123      .09682    0.36   0.716  -.154557  .224982         0
_Ises~_3*|  -.0120564       .0967   -0.12   0.901  -.201579  .177466         0
_Ises~_4*|   .1284934      .09086    1.41   0.157   -.04958  .306567         0
_Ises~_5*|  -.0632334      .09544   -0.66   0.508   -.25029  .123824         0
_Ises~_6*|  -.0225197      .09731   -0.23   0.817  -.213239  .168199         0
_Isess~7*|   -.114486      .09479   -1.21   0.227  -.300276  .071304         0
_Isess~8*|  -.0508659      .09243   -0.55   0.582   -.23203  .130298         0
_Isess~9*|   .1012012      .08873    1.14   0.254  -.072712  .275115         0
_Ises~10*|  -.0745498      .09636   -0.77   0.439  -.263404  .114305         0
_Ises~11*|   .0202348      .09689    0.21   0.835  -.169668  .210138         0
_Ises~12*|  -.1088313      .09599   -1.13   0.257  -.296968  .079305         0
_Ises~13*|   -.120264      .09269   -1.30   0.194  -.301924  .061396         0
_Ises~14*|   .0355628      .09657    0.37   0.713  -.153713  .224839         0
_Ises~15*|   .1254906      .09259    1.36   0.175  -.055978  .306959         0
_Ises~16*|   .0759638      .09561    0.79   0.427  -.111437  .263364         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store vote

. 
. xi: xtprobit VoteInc self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==1 & endowment==100
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -539.62871  
Iteration 1:   log likelihood = -332.91072  
Iteration 2:   log likelihood = -329.96917  
Iteration 3:   log likelihood = -329.96418  
Iteration 4:   log likelihood = -329.96418  

Fitting full model:

rho =  0.0     log likelihood = -329.96418
rho =  0.1     log likelihood = -334.84401

Iteration 0:   log likelihood = -334.84401  
Iteration 1:   log likelihood =  -330.4864  
Iteration 2:   log likelihood = -330.06426  
Iteration 3:   log likelihood = -329.98438  
Iteration 4:   log likelihood = -329.96868  
Iteration 5:   log likelihood = -329.96522  
Iteration 6:   log likelihood = -329.96441  
Iteration 7:   log likelihood = -329.96423  
Iteration 8:   log likelihood = -329.96422  

Random-effects probit regression                Number of obs      =       780
Group variable: Id                              Number of groups   =       156

Random effects u_i ~ Gaussian                   Obs per group: min =         5
                                                               avg =       5.0
                                                               max =         5

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    308.78
Log likelihood  = -329.96422                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
      VoteIncumbent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |   1.213514   .0832403    14.58   0.000     1.050366    1.376662
         self_x_own |  -.4152498   .2060029    -2.02   0.044     -.819008   -.0114917
      self_x_others |  -.0203268   .2105363    -0.10   0.923    -.4329704    .3923167
    self_x_national |  -.2629169   .1539915    -1.71   0.088    -.5647346    .0389009
     own_comm_x_own |   .5039871   .1459232     3.45   0.001     .2179829    .7899912
      fair_x_others |  -.6136335   .1609747    -3.81   0.000    -.9291381   -.2981289
national_x_national |  -.0666116   .1453398    -0.46   0.647    -.3514724    .2182491
        _Isession_2 |  -.3643265   .3555525    -1.02   0.306    -1.061197    .3325435
        _Isession_3 |  -.2548573   .3425759    -0.74   0.457    -.9262938    .4165792
        _Isession_4 |  -.0910446   .3324232    -0.27   0.784    -.7425821    .5604929
        _Isession_5 |  -.3327596   .3155798    -1.05   0.292    -.9512846    .2857653
        _Isession_6 |  -.2941843    .322373    -0.91   0.361    -.9260238    .3376552
        _Isession_7 |  -.6225156   .3405125    -1.83   0.068    -1.289908    .0448766
        _Isession_8 |  -.8166706    .325975    -2.51   0.012     -1.45557   -.1777714
        _Isession_9 |  -.1592925   .3181016    -0.50   0.617    -.7827602    .4641752
       _Isession_10 |  -.2710135   .3511174    -0.77   0.440    -.9591909     .417164
       _Isession_11 |  -.2582095   .3260475    -0.79   0.428    -.8972508    .3808318
       _Isession_12 |  -.4748139   .3478548    -1.36   0.172    -1.156597     .206969
       _Isession_13 |  -.6023543    .333839    -1.80   0.071    -1.256667     .051958
       _Isession_14 |   .3272422   .3688626     0.89   0.375    -.3957151      1.0502
       _Isession_15 |   .2286185   .3244937     0.70   0.481    -.4073776    .8646145
       _Isession_16 |  -.3844599   .3489447    -1.10   0.271    -1.068379    .2994591
              _cons |   .4221514   .2488045     1.70   0.090    -.0654965    .9097992
--------------------+----------------------------------------------------------------
           /lnsig2u |   -14.0712    14.8884                     -43.25193    15.10952
--------------------+----------------------------------------------------------------
            sigma_u |     .00088   .0065508                      4.05e-10    1909.813
                rho |   7.74e-07   .0000115                      1.64e-19    .9999997
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     0.00 Prob >= chibar2 = 1.000

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(VoteIncumbent=1 assuming u_i=0) (predict, pu0)
         =  .66354273
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .4428499      .05527    8.01   0.000   .334514  .551186         0
self_x~n |  -.1515379       .0766   -1.98   0.048  -.301664 -.001412         0
self_x~s |  -.0074179      .07688   -0.10   0.923  -.158097  .143261         0
self_x~l |  -.0959468      .05682   -1.69   0.091  -.207311  .015417         0
own_co~n |    .183921      .05518    3.33   0.001   .075767  .292074         0
fair_x~s |  -.2239345      .06226   -3.60   0.000  -.345955 -.101914         0
n~_x_n~l |  -.0243087      .05317   -0.46   0.648  -.128511  .079893         0
_Ises~_2*|  -.1404868      .13592   -1.03   0.301  -.406879  .125906         0
_Ises~_3*|  -.0971121      .12973   -0.75   0.454  -.351386  .157162         0
_Ises~_4*|  -.0338247      .12319   -0.27   0.784  -.275274  .207625         0
_Ises~_5*|   -.127928      .11915   -1.07   0.283  -.361457  .105601         0
_Ises~_6*|  -.1126302      .12168   -0.93   0.355  -.351113  .125852         0
_Isess~7*|  -.2429449      .12844   -1.89   0.059  -.494683  .008793         0
_Isess~8*|  -.3169439      .11953   -2.65   0.008  -.551211 -.082677         0
_Isess~9*|  -.0598724      .11865   -0.50   0.614  -.292422  .172677         0
_Ises~10*|  -.1034762      .13339   -0.78   0.438  -.364917  .157964         0
_Ises~11*|  -.0984312        .123   -0.80   0.424  -.339512   .14265         0
_Ises~12*|  -.1845423      .13274   -1.39   0.164  -.444715   .07563         0
_Ises~13*|  -.2350461      .12601   -1.87   0.062  -.482027  .011935         0
_Ises~14*|   .1096473      .12233    0.90   0.370  -.130121  .349415         0
_Ises~15*|   .0788597        .113    0.70   0.485  -.142624  .300343         0
_Ises~16*|  -.1485096      .13323   -1.11   0.265   -.40964  .112621         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store vote_poor

. 
. xi: xtprobit VoteInc self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==1 & endowment==500
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -287.89449  
Iteration 1:   log likelihood = -213.90597  
Iteration 2:   log likelihood = -213.21994  
Iteration 3:   log likelihood = -213.21723  
Iteration 4:   log likelihood = -213.21723  

Fitting full model:

rho =  0.0     log likelihood = -213.21723
rho =  0.1     log likelihood = -215.16568

Iteration 0:   log likelihood = -215.16568  
Iteration 1:   log likelihood = -213.57273  
Iteration 2:   log likelihood = -213.25445  
Iteration 3:   log likelihood = -213.22451  
Iteration 4:   log likelihood = -213.21894  
Iteration 5:   log likelihood = -213.21762  
Iteration 6:   log likelihood = -213.21731  
Iteration 7:   log likelihood = -213.21724  
Iteration 8:   log likelihood = -213.21724  

Random-effects probit regression                Number of obs      =       420
Group variable: Id                              Number of groups   =        84

Random effects u_i ~ Gaussian                   Obs per group: min =         5
                                                               avg =       5.0
                                                               max =         5

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    121.60
Log likelihood  = -213.21724                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
      VoteIncumbent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |   .8185541   .0973252     8.41   0.000     .6278003    1.009308
         self_x_own |  -.4969079   .2540665    -1.96   0.050    -.9948691    .0010533
      self_x_others |  -.2287233   .2827828    -0.81   0.419    -.7829675    .3255209
    self_x_national |   .0842721   .1980816     0.43   0.671    -.3039607    .4725049
     own_comm_x_own |   .3743295   .1918667     1.95   0.051    -.0017224    .7503815
      fair_x_others |  -.3372626   .2128066    -1.58   0.113    -.7543559    .0798308
national_x_national |   .3812053   .1815564     2.10   0.036     .0253613    .7370493
        _Isession_2 |    .553659   .3629254     1.53   0.127    -.1576618     1.26498
        _Isession_3 |   .4348328   .3740918     1.16   0.245    -.2983736    1.168039
        _Isession_4 |   1.204831   .4130759     2.92   0.004     .3952167    2.014445
        _Isession_5 |   -.147584   .4492699    -0.33   0.743    -1.028137    .7329689
        _Isession_6 |   .0336762   .4812659     0.07   0.944    -.9095877    .9769401
        _Isession_7 |    .119202   .3580036     0.33   0.739    -.5824721    .8208761
        _Isession_8 |   .8130509   .3642906     2.23   0.026     .0990544    1.527047
        _Isession_9 |    .779323   .3587825     2.17   0.030     .0761222    1.482524
       _Isession_10 |  -.0640746   .3586709    -0.18   0.858    -.7670567    .6389076
       _Isession_11 |   .2403181   .4480362     0.54   0.592    -.6378169    1.118453
       _Isession_12 |   .1143048   .3646079     0.31   0.754    -.6003135    .8289232
       _Isession_13 |   .1107471   .3480075     0.32   0.750     -.571335    .7928293
       _Isession_14 |  -.0952087   .3654934    -0.26   0.794    -.8115625    .6211452
       _Isession_15 |   .3635621   .4533985     0.80   0.423    -.5250826    1.252207
       _Isession_16 |   .7023391   .3704024     1.90   0.058    -.0236363    1.428314
              _cons |  -.2254668   .2512003    -0.90   0.369    -.7178103    .2668767
--------------------+----------------------------------------------------------------
           /lnsig2u |  -15.14954   20.12182                     -54.58758    24.28849
--------------------+----------------------------------------------------------------
            sigma_u |   .0005132   .0051636                      1.40e-12      188009
                rho |   2.63e-07   5.30e-06                      1.96e-24           1
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     0.00 Prob >= chibar2 = 1.000

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(VoteIncumbent=1 assuming u_i=0) (predict, pu0)
         =  .41080807
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .3183602      .04223    7.54   0.000   .235589  .401131         0
self_x~n |  -.1932623      .09911   -1.95   0.051  -.387513  .000988         0
self_x~s |  -.0889573      .10996   -0.81   0.419  -.304472  .126557         0
self_x~l |   .0327759      .07701    0.43   0.670  -.118157  .183709         0
own_co~n |   .1455879       .0751    1.94   0.053  -.001608  .292784         0
fair_x~s |  -.1311715      .08349   -1.57   0.116  -.294815  .032472         0
n~_x_n~l |   .1482621      .07142    2.08   0.038   .008287  .288237         0
_Ises~_2*|   .2178087      .13907    1.57   0.117  -.054767  .490384         0
_Ises~_3*|   .1721106      .14577    1.18   0.238  -.113601  .457822         0
_Ises~_4*|   .4254918      .12705    3.35   0.001   .176484    .6745         0
_Ises~_5*|  -.0562527      .16958   -0.33   0.740  -.388633  .276128         0
_Ises~_6*|   .0131451      .18814    0.07   0.944  -.355596  .381886         0
_Isess~7*|    .046878      .14065    0.33   0.739  -.228799  .322555         0
_Isess~8*|   .3107862      .13184    2.36   0.018   .052391  .569181         0
_Isess~9*|   .2993533      .13126    2.28   0.023   .042087   .55662         0
_Ises~10*|  -.0247245      .13833   -0.18   0.858  -.295855  .246406         0
_Ises~11*|   .0951165      .17733    0.54   0.592  -.252449  .442682         0
_Ises~12*|   .0449359      .14326    0.31   0.754  -.235855  .325727         0
_Ises~13*|   .0435256      .13659    0.32   0.750  -.224187  .311238         0
_Ises~14*|  -.0365799      .14026   -0.26   0.794  -.311475  .238315         0
_Ises~15*|   .1441094       .1783    0.81   0.419  -.205343  .493562         0
_Ises~16*|   .2724654      .13765    1.98   0.048   .002671   .54226         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store vote_rich

. 
. xi: xtprobit approve self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==0
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -1809.7291  
Iteration 1:   log likelihood = -1286.1269  
Iteration 2:   log likelihood = -1284.2207  
Iteration 3:   log likelihood = -1284.2197  
Iteration 4:   log likelihood = -1284.2197  

Fitting full model:

rho =  0.0     log likelihood = -1284.2197
rho =  0.1     log likelihood = -1252.6361
rho =  0.2     log likelihood = -1249.8752
rho =  0.3     log likelihood = -1258.8733

Iteration 0:   log likelihood = -1249.8761  
Iteration 1:   log likelihood = -1244.8293  
Iteration 2:   log likelihood = -1244.8214  
Iteration 3:   log likelihood = -1244.8214  

Random-effects probit regression                Number of obs      =      2640
Group variable: Id                              Number of groups   =       240

Random effects u_i ~ Gaussian                   Obs per group: min =        11
                                                               avg =      11.0
                                                               max =        11

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    790.58
Log likelihood  = -1244.8214                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
            approve |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |   1.128477   .0445786    25.31   0.000     1.041104    1.215849
         self_x_own |   -.321412   .1113172    -2.89   0.004    -.5395897   -.1032343
      self_x_others |  -.1480765   .1142121    -1.30   0.195    -.3719281    .0757751
    self_x_national |  -.3368114   .0801361    -4.20   0.000    -.4938753   -.1797474
     own_comm_x_own |   .3209536   .0784331     4.09   0.000     .1672276    .4746796
      fair_x_others |  -.1553363   .0810896    -1.92   0.055     -.314269    .0035963
national_x_national |   .2110806   .0692459     3.05   0.002     .0753612       .3468
        _Isession_2 |  -.2603171   .2461549    -1.06   0.290    -.7427718    .2221376
        _Isession_3 |  -.0846543   .2453563    -0.35   0.730    -.5655438    .3962352
        _Isession_4 |   .0285337   .2467939     0.12   0.908    -.4551736    .5122409
        _Isession_5 |  -.2750311   .2452481    -1.12   0.262    -.7557087    .2056464
        _Isession_6 |  -.3484428   .2458043    -1.42   0.156    -.8302103    .1333248
        _Isession_7 |   .0482962    .248081     0.19   0.846    -.4379335    .5345259
        _Isession_8 |  -.4430307   .2456654    -1.80   0.071     -.924526    .0384647
        _Isession_9 |   .2107785    .242713     0.87   0.385    -.2649302    .6864873
       _Isession_10 |  -.3016053   .2451257    -1.23   0.219    -.7820429    .1788323
       _Isession_11 |  -.3228457   .2454263    -1.32   0.188    -.8038725    .1581811
       _Isession_12 |  -.1374842   .2473609    -0.56   0.578    -.6223027    .3473343
       _Isession_13 |    .201817   .2430851     0.83   0.406    -.2746211    .6782552
       _Isession_14 |  -.0293761    .250059    -0.12   0.906    -.5194827    .4607305
       _Isession_15 |  -.0672969   .2454808    -0.27   0.784    -.5484305    .4138367
       _Isession_16 |   .0486434    .246537     0.20   0.844    -.4345603    .5318471
              _cons |   .3094534   .1736265     1.78   0.075    -.0308483    .6497552
--------------------+----------------------------------------------------------------
           /lnsig2u |  -1.438842   .1911385                     -1.813466   -1.064217
--------------------+----------------------------------------------------------------
            sigma_u |   .4870342   .0465455                      .4038413    .5873651
                rho |   .1917248     .02962                      .1402197    .2565044
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =    78.80 Prob >= chibar2 = 0.000

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(approve=1 assuming u_i=0) (predict, pu0)
         =  .62151169
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .4291493      .02829   15.17   0.000   .373708  .484591         0
self_x~n |    -.12223      .04275   -2.86   0.004  -.206018 -.038442         0
self_x~s |  -.0563121      .04358   -1.29   0.196  -.141723  .029098         0
self_x~l |  -.1280862      .03118   -4.11   0.000  -.189198 -.066975         0
own_co~n |   .1220557       .0302    4.04   0.000   .062859  .181252         0
fair_x~s |   -.059073      .03097   -1.91   0.056  -.119775  .001629         0
n~_x_n~l |    .080272      .02655    3.02   0.002   .028241  .132303         0
_Ises~_2*|   -.101917      .09588   -1.06   0.288  -.289845  .086011         0
_Ises~_3*|  -.0325794      .09438   -0.35   0.730  -.217558    .1524         0
_Ises~_4*|   .0108019      .09342    0.12   0.908  -.172294  .193898         0
_Ises~_5*|  -.1077819      .09554   -1.13   0.259  -.295037  .079473         0
_Ises~_6*|  -.1370622      .09576   -1.43   0.152  -.324741  .050617         0
_Isess~7*|    .018223      .09358    0.19   0.846  -.165184  .201629         0
_Isess~8*|  -.1746432       .0953   -1.83   0.067  -.361428  .012142         0
_Isess~9*|   .0770374       .0886    0.87   0.385  -.096618  .250693         0
_Ises~10*|  -.1183808      .09552   -1.24   0.215  -.305605  .068843         0
_Ises~11*|  -.1268543      .09564   -1.33   0.185  -.314303  .060595         0
_Ises~12*|  -.0532426      .09569   -0.56   0.578  -.240793  .134308         0
_Ises~13*|   .0739075      .08892    0.83   0.406  -.100365   .24818         0
_Ises~14*|  -.0112208      .09552   -0.12   0.906  -.198445  .176003         0
_Ises~15*|  -.0258411      .09423   -0.27   0.784   -.21053  .158847         0
_Ises~16*|   .0183529        .093    0.20   0.844   -.16392  .200625         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store approve

. 
. xi: xtprobit approve self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==0 & endowment==100
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -1177.0459  
Iteration 1:   log likelihood = -818.03843  
Iteration 2:   log likelihood = -816.30373  
Iteration 3:   log likelihood = -816.30189  
Iteration 4:   log likelihood = -816.30189  

Fitting full model:

rho =  0.0     log likelihood = -816.30189
rho =  0.1     log likelihood = -801.92206
rho =  0.2     log likelihood =  -803.2675

Iteration 0:   log likelihood = -801.92206  
Iteration 1:   log likelihood = -799.91689  
Iteration 2:   log likelihood = -799.70546  
Iteration 3:   log likelihood = -799.70464  
Iteration 4:   log likelihood = -799.70464  

Random-effects probit regression                Number of obs      =      1716
Group variable: Id                              Number of groups   =       156

Random effects u_i ~ Gaussian                   Obs per group: min =        11
                                                               avg =      11.0
                                                               max =        11

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    533.71
Log likelihood  = -799.70464                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
            approve |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |    1.16488   .0549109    21.21   0.000     1.057257    1.272503
         self_x_own |  -.2712761     .13945    -1.95   0.052    -.5445931     .002041
      self_x_others |   -.294009   .1365172    -2.15   0.031    -.5615777   -.0264402
    self_x_national |  -.3867324   .1010726    -3.83   0.000     -.584831   -.1886338
     own_comm_x_own |   .2796528   .0997862     2.80   0.005     .0840755    .4752301
      fair_x_others |  -.1408753   .0974697    -1.45   0.148    -.3319125    .0501619
national_x_national |   .0352386   .0890764     0.40   0.692    -.1393479    .2098251
        _Isession_2 |  -.2622579   .2969552    -0.88   0.377    -.8442793    .3197636
        _Isession_3 |   .1061795   .2967462     0.36   0.720    -.4754324    .6877914
        _Isession_4 |  -.1039235   .2975397    -0.35   0.727    -.6870905    .4792436
        _Isession_5 |  -.2261509   .2762373    -0.82   0.413     -.767566    .3152643
        _Isession_6 |  -.2760349     .27754    -0.99   0.320    -.8200033    .2679334
        _Isession_7 |  -.0672966   .3031466    -0.22   0.824    -.6614531    .5268599
        _Isession_8 |  -.2326376   .2981491    -0.78   0.435     -.816999    .3517238
        _Isession_9 |   .1173009   .2913853     0.40   0.687    -.4538039    .6884057
       _Isession_10 |  -.1325836   .2963671    -0.45   0.655    -.7134525    .4482853
       _Isession_11 |  -.1332854   .2781025    -0.48   0.632    -.6783563    .4117855
       _Isession_12 |  -.1291093   .2991482    -0.43   0.666    -.7154289    .4572103
       _Isession_13 |   .0703793   .2920151     0.24   0.810    -.5019598    .6427184
       _Isession_14 |   .2434949   .3056442     0.80   0.426    -.3555567    .8425465
       _Isession_15 |   .0338443   .2773954     0.12   0.903    -.5098407    .5775293
       _Isession_16 |  -.0142193   .2958015    -0.05   0.962    -.5939796    .5655409
              _cons |   .2450285   .2101004     1.17   0.244    -.1667607    .6568177
--------------------+----------------------------------------------------------------
           /lnsig2u |  -1.722268   .2691566                     -2.249805   -1.194731
--------------------+----------------------------------------------------------------
            sigma_u |   .4226825   .0568839                      .3246841    .5502595
                rho |   .1515793   .0346143                      .0953663    .2324139
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =    33.19 Prob >= chibar2 = 0.000

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(approve=1 assuming u_i=0) (predict, pu0)
         =  .59678283
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .4509765      .03128   14.42   0.000   .389674  .512279         0
self_x~n |   -.105023      .05411   -1.94   0.052  -.211077  .001031         0
self_x~s |  -.1138239      .05304   -2.15   0.032  -.217789 -.009858         0
self_x~l |  -.1497212      .03985   -3.76   0.000  -.227827 -.071615         0
own_co~n |   .1082659      .03869    2.80   0.005   .032439  .184093         0
fair_x~s |  -.0545391      .03777   -1.44   0.149  -.128573  .019495         0
n~_x_n~l |   .0136424      .03448    0.40   0.692  -.053932  .081217         0
_Ises~_2*|   -.103656      .11672   -0.89   0.374  -.332416  .125104         0
_Ises~_3*|    .040501      .11312    0.36   0.720  -.181207  .262209         0
_Ises~_4*|  -.0406763      .11637   -0.35   0.727  -.268762  .187409         0
_Ises~_5*|  -.0892522      .10832   -0.82   0.410  -.301549  .123045         0
_Ises~_6*|  -.1091506      .10883   -1.00   0.316  -.322448  .104146         0
_Isess~7*|  -.0262496      .11824   -0.22   0.824  -.257991  .205492         0
_Isess~8*|  -.0918397      .11721   -0.78   0.433  -.321564  .137885         0
_Isess~9*|   .0446642      .11092    0.40   0.687  -.172744  .262073         0
_Ises~10*|  -.0520181      .11611   -0.45   0.654  -.279593  .175556         0
_Ises~11*|  -.0522964      .10878   -0.48   0.631  -.265508  .160915         0
_Ises~12*|  -.0506411       .1172   -0.43   0.666  -.280357  .179075         0
_Ises~13*|   .0269912      .11199    0.24   0.810  -.192508   .24649         0
_Ises~14*|   .0906276      .11311    0.80   0.423  -.131063  .312318         0
_Ises~15*|   .0130459      .10699    0.12   0.903  -.196652  .222744         0
_Ises~16*|  -.0055143      .11471   -0.05   0.962  -.230343  .219314         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store approve_poor

. 
. xi: xtprobit approve self  self_x_own self_x_others self_x_national  own_comm_x_own   fair_x_others
>  national_x_national i.session if election==0 & endowment==500
i.session         _Isession_1-16      (naturally coded; _Isession_1 omitted)

Fitting comparison model:

Iteration 0:   log likelihood = -632.65373  
Iteration 1:   log likelihood = -447.61337  
Iteration 2:   log likelihood =  -446.0607  
Iteration 3:   log likelihood = -446.05641  
Iteration 4:   log likelihood = -446.05641  

Fitting full model:

rho =  0.0     log likelihood = -446.05641
rho =  0.1     log likelihood = -432.33597
rho =  0.2     log likelihood = -429.69307
rho =  0.3     log likelihood = -431.55169

Iteration 0:   log likelihood =  -429.6934  
Iteration 1:   log likelihood = -427.84648  
Iteration 2:   log likelihood = -427.84079  
Iteration 3:   log likelihood = -427.84079  

Random-effects probit regression                Number of obs      =       924
Group variable: Id                              Number of groups   =        84

Random effects u_i ~ Gaussian                   Obs per group: min =        11
                                                               avg =      11.0
                                                               max =        11

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(22)      =    271.73
Log likelihood  = -427.84079                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
            approve |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
               self |   1.083246   .0771674    14.04   0.000     .9320009    1.234491
         self_x_own |  -.4806939   .1941154    -2.48   0.013    -.8611532   -.1002346
      self_x_others |   .2188111   .2228377     0.98   0.326    -.2179428     .655565
    self_x_national |  -.2637352   .1358917    -1.94   0.052    -.5300781    .0026077
     own_comm_x_own |   .4805639   .1361759     3.53   0.000     .2136642    .7474637
      fair_x_others |  -.3077311   .1636061    -1.88   0.060    -.6283931    .0129309
national_x_national |   .4716486   .1206309     3.91   0.000     .2352164    .7080809
        _Isession_2 |   -.354555    .420282    -0.84   0.399    -1.178293    .4691825
        _Isession_3 |  -.4134541   .4171774    -0.99   0.322    -1.231107    .4041986
        _Isession_4 |   .2181605   .4252326     0.51   0.608    -.6152802    1.051601
        _Isession_5 |  -.2815155    .514282    -0.55   0.584     -1.28949    .7264587
        _Isession_6 |  -.4960532   .5144904    -0.96   0.335    -1.504436    .5123294
        _Isession_7 |   .1238326   .4152506     0.30   0.766    -.6900436    .9377088
        _Isession_8 |   -.815038   .4154205    -1.96   0.050    -1.629247   -.0008287
        _Isession_9 |   .2562091   .4128289     0.62   0.535    -.5529208    1.065339
       _Isession_10 |  -.6601196   .4165968    -1.58   0.113    -1.476634     .156395
       _Isession_11 |  -.9032811   .5005048    -1.80   0.071    -1.884253    .0776903
       _Isession_12 |  -.2192124   .4174154    -0.53   0.599    -1.037331    .5989067
       _Isession_13 |   .3463845   .4136893     0.84   0.402    -.4644317    1.157201
       _Isession_14 |  -.5376336   .4263399    -1.26   0.207    -1.373244    .2979771
       _Isession_15 |  -.3371374   .5090776    -0.66   0.508    -1.334911    .6606363
       _Isession_16 |   .0557064   .4225013     0.13   0.895     -.772381    .8837938
              _cons |   .4794651   .2964316     1.62   0.106    -.1015302     1.06046
--------------------+----------------------------------------------------------------
           /lnsig2u |  -1.217913   .3024936                      -1.81079   -.6250365
--------------------+----------------------------------------------------------------
            sigma_u |   .5439181   .0822659                      .4043822    .7316023
                rho |   .2283039   .0532937                      .1405427    .3486368
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =    36.43 Prob >= chibar2 = 0.000

. mfx, pred(pu0) at(zero)

Marginal effects after xtprobit
      y  = Pr(approve=1 assuming u_i=0) (predict, pu0)
         =  .68419611
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    self |   .3852281      .06011    6.41   0.000   .267406   .50305         0
self_x~n |  -.1709462      .07335   -2.33   0.020  -.314719 -.027174         0
self_x~s |   .0778144      .07902    0.98   0.325  -.077067  .232696         0
self_x~l |  -.0937905       .0499   -1.88   0.060  -.191586  .004005         0
own_co~n |      .1709      .05276    3.24   0.001   .067485  .274315         0
fair_x~s |  -.1094365      .05957   -1.84   0.066  -.226193   .00732         0
n~_x_n~l |   .1677295      .04877    3.44   0.001    .07214  .263319         0
_Ises~_2*|  -.1344935      .15818   -0.85   0.395  -.444529  .175542         0
_Ises~_3*|  -.1578806      .15738   -1.00   0.316  -.466336  .150575         0
_Ises~_4*|   .0730982      .14205    0.51   0.607  -.205322  .351518         0
_Ises~_5*|  -.1057383      .19532   -0.54   0.588  -.488556  .277079         0
_Ises~_6*|  -.1908135      .19813   -0.96   0.336  -.579134  .197507         0
_Isess~7*|   .0426486      .14303    0.30   0.766  -.237687  .322984         0
_Isess~8*|  -.3155996      .15218   -2.07   0.038  -.613863 -.017336         0
_Isess~9*|   .0848394      .13691    0.62   0.535  -.183493  .353171         0
_Ises~10*|  -.2558767      .15584   -1.64   0.101  -.561323  .049569         0
_Ises~11*|  -.3483461      .18094   -1.93   0.054  -.702983  .006291         0
_Ises~12*|  -.0815305      .15486   -0.53   0.599  -.385052   .22199         0
_Ises~13*|   .1113592      .13334    0.84   0.404  -.149979  .372697         0
_Ises~14*|  -.2073889      .16123   -1.29   0.198  -.523389  .108611         0
_Ises~15*|  -.1276067      .19448   -0.66   0.512  -.508774   .25356         0
_Ises~16*|   .0195383      .14813    0.13   0.895  -.270801  .309877         0
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

. est store approve_rich

. 
. estout vote vote_poor vote_rich, cells(b(star fmt(3)) se(par fmt(3)))   starlevels(+ 0.10 * 0.05 **
>  0.01)    legend label varlabels(_cons constant) margin stats(r2 N) style(tex)

                    &        vote  &   vote_poor  &   vote_rich  \\
                    &        b/se  &        b/se  &        b/se  \\
VoteIncumbent       &              &              &              \\
self                &       0.407**&       0.443**&       0.318**\\
                    &     (0.025)  &     (0.055)  &     (0.042)  \\
self_x_own          &      -0.148* &      -0.152* &      -0.193+ \\
                    &     (0.061)  &     (0.077)  &     (0.099)  \\
self_x_others       &      -0.018  &      -0.007  &      -0.089  \\
                    &     (0.064)  &     (0.077)  &     (0.110)  \\
self_x_national     &      -0.060  &      -0.096+ &       0.033  \\
                    &     (0.046)  &     (0.057)  &     (0.077)  \\
own_comm_x_own      &       0.167**&       0.184**&       0.146+ \\
                    &     (0.043)  &     (0.055)  &     (0.075)  \\
fair_x_others       &      -0.203**&      -0.224**&      -0.131  \\
                    &     (0.048)  &     (0.062)  &     (0.083)  \\
national_x_national &       0.028  &      -0.024  &       0.148* \\
                    &     (0.042)  &     (0.053)  &     (0.071)  \\
session==2 (d)      &       0.035  &      -0.140  &       0.218  \\
                    &     (0.097)  &     (0.136)  &     (0.139)  \\
session==3 (d)      &      -0.012  &      -0.097  &       0.172  \\
                    &     (0.097)  &     (0.130)  &     (0.146)  \\
session==4 (d)      &       0.128  &      -0.034  &       0.425**\\
                    &     (0.091)  &     (0.123)  &     (0.127)  \\
session==5 (d)      &      -0.063  &      -0.128  &      -0.056  \\
                    &     (0.095)  &     (0.119)  &     (0.170)  \\
session==6 (d)      &      -0.023  &      -0.113  &       0.013  \\
                    &     (0.097)  &     (0.122)  &     (0.188)  \\
session==7 (d)      &      -0.114  &      -0.243+ &       0.047  \\
                    &     (0.095)  &     (0.128)  &     (0.141)  \\
session==8 (d)      &      -0.051  &      -0.317**&       0.311* \\
                    &     (0.092)  &     (0.120)  &     (0.132)  \\
session==9 (d)      &       0.101  &      -0.060  &       0.299* \\
                    &     (0.089)  &     (0.119)  &     (0.131)  \\
session==10 (d)     &      -0.075  &      -0.103  &      -0.025  \\
                    &     (0.096)  &     (0.133)  &     (0.138)  \\
session==11 (d)     &       0.020  &      -0.098  &       0.095  \\
                    &     (0.097)  &     (0.123)  &     (0.177)  \\
session==12 (d)     &      -0.109  &      -0.185  &       0.045  \\
                    &     (0.096)  &     (0.133)  &     (0.143)  \\
session==13 (d)     &      -0.120  &      -0.235+ &       0.044  \\
                    &     (0.093)  &     (0.126)  &     (0.137)  \\
session==14 (d)     &       0.036  &       0.110  &      -0.037  \\
                    &     (0.097)  &     (0.122)  &     (0.140)  \\
session==15 (d)     &       0.125  &       0.079  &       0.144  \\
                    &     (0.093)  &     (0.113)  &     (0.178)  \\
session==16 (d)     &       0.076  &      -0.149  &       0.272* \\
                    &     (0.096)  &     (0.133)  &     (0.138)  \\
constant            &              &              &              \\
                    &              &              &              \\
lnsig2u             &              &              &              \\
constant            &              &              &              \\
                    &              &              &              \\
r2                  &              &              &              \\
N                   &    1200.000  &     780.000  &     420.000  \\
(d) for discrete change of dummy variable from 0 to 1
+ p<0.10, * p<0.05, ** p<0.01

. estout approve approve_poor approve_rich, cells(b(star fmt(3)) se(par fmt(3)))   starlevels(+ 0.10 
> * 0.05 ** 0.01)    legend label varlabels(_cons constant) margin stats(r2 N) style(tex)

                    &     approve  &approve_poor  &approve_rich  \\
                    &        b/se  &        b/se  &        b/se  \\
approve             &              &              &              \\
self                &       0.429**&       0.451**&       0.385**\\
                    &     (0.028)  &     (0.031)  &     (0.060)  \\
self_x_own          &      -0.122**&      -0.105+ &      -0.171* \\
                    &     (0.043)  &     (0.054)  &     (0.073)  \\
self_x_others       &      -0.056  &      -0.114* &       0.078  \\
                    &     (0.044)  &     (0.053)  &     (0.079)  \\
self_x_national     &      -0.128**&      -0.150**&      -0.094+ \\
                    &     (0.031)  &     (0.040)  &     (0.050)  \\
own_comm_x_own      &       0.122**&       0.108**&       0.171**\\
                    &     (0.030)  &     (0.039)  &     (0.053)  \\
fair_x_others       &      -0.059+ &      -0.055  &      -0.109+ \\
                    &     (0.031)  &     (0.038)  &     (0.060)  \\
national_x_national &       0.080**&       0.014  &       0.168**\\
                    &     (0.027)  &     (0.034)  &     (0.049)  \\
session==2 (d)      &      -0.102  &      -0.104  &      -0.134  \\
                    &     (0.096)  &     (0.117)  &     (0.158)  \\
session==3 (d)      &      -0.033  &       0.041  &      -0.158  \\
                    &     (0.094)  &     (0.113)  &     (0.157)  \\
session==4 (d)      &       0.011  &      -0.041  &       0.073  \\
                    &     (0.093)  &     (0.116)  &     (0.142)  \\
session==5 (d)      &      -0.108  &      -0.089  &      -0.106  \\
                    &     (0.096)  &     (0.108)  &     (0.195)  \\
session==6 (d)      &      -0.137  &      -0.109  &      -0.191  \\
                    &     (0.096)  &     (0.109)  &     (0.198)  \\
session==7 (d)      &       0.018  &      -0.026  &       0.043  \\
                    &     (0.094)  &     (0.118)  &     (0.143)  \\
session==8 (d)      &      -0.175+ &      -0.092  &      -0.316* \\
                    &     (0.095)  &     (0.117)  &     (0.152)  \\
session==9 (d)      &       0.077  &       0.045  &       0.085  \\
                    &     (0.089)  &     (0.111)  &     (0.137)  \\
session==10 (d)     &      -0.118  &      -0.052  &      -0.256  \\
                    &     (0.096)  &     (0.116)  &     (0.156)  \\
session==11 (d)     &      -0.127  &      -0.052  &      -0.348+ \\
                    &     (0.096)  &     (0.109)  &     (0.181)  \\
session==12 (d)     &      -0.053  &      -0.051  &      -0.082  \\
                    &     (0.096)  &     (0.117)  &     (0.155)  \\
session==13 (d)     &       0.074  &       0.027  &       0.111  \\
                    &     (0.089)  &     (0.112)  &     (0.133)  \\
session==14 (d)     &      -0.011  &       0.091  &      -0.207  \\
                    &     (0.096)  &     (0.113)  &     (0.161)  \\
session==15 (d)     &      -0.026  &       0.013  &      -0.128  \\
                    &     (0.094)  &     (0.107)  &     (0.194)  \\
session==16 (d)     &       0.018  &      -0.006  &       0.020  \\
                    &     (0.093)  &     (0.115)  &     (0.148)  \\
constant            &              &              &              \\
                    &              &              &              \\
lnsig2u             &              &              &              \\
constant            &              &              &              \\
                    &              &              &              \\
r2                  &              &              &              \\
N                   &    2640.000  &    1716.000  &     924.000  \\
(d) for discrete change of dummy variable from 0 to 1
+ p<0.10, * p<0.05, ** p<0.01

. 
. ***********
. * Table 7 *
. ***********
. 
. *gen positive_own=1 if IncumbentAdvantage>0
. *replace positive_own=0 if IncumbentAdvantage<0
. 
. drop Incumb_Opt_Tax_Dist Cand_Opt_Tax_Dist

. 
. * Creating a variable for distance between incumbent tax rate and optimal tax *
. * Optimal Tax is 20% *
. 
. generate Incumb_Opt_Tax_Dist = .
(3840 missing values generated)

. replace Incumb_Opt_Tax_Dist = abs(20-tax_rate_1) if current_incumbent == 1
(2160 real changes made)

. replace Incumb_Opt_Tax_Dist = abs(20-tax_rate_2) if current_incumbent == 2
(1680 real changes made)

. 
. * Creating a variable for distance between candidate tax rate and optimal tax *
. * Optimal Tax is 20% *
. 
. generate Cand_Opt_Tax_Dist = .
(3840 missing values generated)

. replace Cand_Opt_Tax_Dist = abs(20-tax_rate_2) if current_incumbent == 1
(2160 real changes made)

. replace Cand_Opt_Tax_Dist = abs(20-tax_rate_1) if current_incumbent == 2
(1680 real changes made)

. 
. gen owncom = avg_delta_welfare_own_communi71 if current_incumbent == 1
(1680 missing values generated)

. replace owncom = avg_delta_welfare_own_communi72 if current_incumbent == 2
(1680 real changes made)

. 
. gen netgain = delta_own_welfare_1 if current_incumbent == 1
(1680 missing values generated)

. replace netgain = delta_own_welfare_2 if current_incumbent == 2
(1680 real changes made)

. 
. xtprobit VoteInc IncumbentAdvantage owncom Incumb_Opt_Tax_Dist Cand_Opt_Tax_Dist fair_inc fair_cand
>  endowment if election == 1

Fitting comparison model:

Iteration 0:   log likelihood = -828.24649  
Iteration 1:   log likelihood = -712.94579  
Iteration 2:   log likelihood = -708.40167  
Iteration 3:   log likelihood = -708.39274  
Iteration 4:   log likelihood = -708.39274  

Fitting full model:

rho =  0.0     log likelihood = -708.39274
rho =  0.1     log likelihood = -710.72244

Iteration 0:   log likelihood = -710.72244  
Iteration 1:   log likelihood = -708.64978  
Iteration 2:   log likelihood = -708.33709  
Iteration 3:   log likelihood = -708.29256  
Iteration 4:   log likelihood = -708.28999  
Iteration 5:   log likelihood = -708.28998  

Random-effects probit regression                Number of obs      =      1200
Group variable: Id                              Number of groups   =       240

Random effects u_i ~ Gaussian                   Obs per group: min =         5
                                                               avg =       5.0
                                                               max =         5

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(7)       =    141.45
Log likelihood  = -708.28998                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
      VoteIncumbent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
 IncumbentAdvantage |   .0135035   .0013488    10.01   0.000     .0108599    .0161471
             owncom |   .0135477   .0028245     4.80   0.000     .0080117    .0190836
Incumb_Opt_Tax_Dist |  -.0096391   .0051937    -1.86   0.063    -.0198186    .0005405
  Cand_Opt_Tax_Dist |  -.0017098    .003578    -0.48   0.633    -.0087225    .0053029
           fair_inc |   .0034949    .001775     1.97   0.049     .0000159    .0069739
          fair_cand |  -.0026512   .0018892    -1.40   0.161    -.0063539    .0010516
          endowment |   .0000353   .0002163     0.16   0.870    -.0003887    .0004593
              _cons |   .1004729   .0935949     1.07   0.283    -.0829698    .2839157
--------------------+----------------------------------------------------------------
           /lnsig2u |   -4.02375   2.287564                     -8.507293    .4597923
--------------------+----------------------------------------------------------------
            sigma_u |   .1337377   .1529667                      .0142123    1.258469
                rho |   .0175715   .0394896                      .0002019    .6129649
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     0.21 Prob >= chibar2 = 0.325

. 
. xtprobit VoteInc IncumbentAdvantage owncom Incumb_Opt_Tax_Dist Cand_Opt_Tax_Dist fair_inc fair_cand
>  endowment if election == 1 & netgain < 0

Fitting comparison model:

Iteration 0:   log likelihood = -281.46068  
Iteration 1:   log likelihood =  -239.3423  
Iteration 2:   log likelihood = -233.61841  
Iteration 3:   log likelihood = -233.56208  
Iteration 4:   log likelihood = -233.56205  
Iteration 5:   log likelihood = -233.56205  

Fitting full model:

rho =  0.0     log likelihood = -233.56205
rho =  0.1     log likelihood = -233.86317

Iteration 0:   log likelihood = -233.86317  
Iteration 1:   log likelihood = -233.34571  
Iteration 2:   log likelihood = -233.31344  
Iteration 3:   log likelihood = -233.31242  
Iteration 4:   log likelihood = -233.31241  

Random-effects probit regression                Number of obs      =       407
Group variable: Id                              Number of groups   =        96

Random effects u_i ~ Gaussian                   Obs per group: min =         1
                                                               avg =       4.2
                                                               max =         5

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(7)       =     47.15
Log likelihood  = -233.31241                    Prob > chi2        =    0.0000

-------------------------------------------------------------------------------------
      VoteIncumbent |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
 IncumbentAdvantage |   .0075362    .002035     3.70   0.000     .0035476    .0115248
             owncom |   .0182285   .0048067     3.79   0.000     .0088075    .0276494
Incumb_Opt_Tax_Dist |  -.0279904   .0109082    -2.57   0.010    -.0493701   -.0066106
  Cand_Opt_Tax_Dist |   .0063996   .0091751     0.70   0.485    -.0115831    .0243824
           fair_inc |   .0033908   .0031003     1.09   0.274    -.0026858    .0094673
          fair_cand |  -.0042773   .0033303    -1.28   0.199    -.0108045      .00225
          endowment |  -.0031964   .0016648    -1.92   0.055    -.0064595    .0000666
              _cons |   1.664457   .8306326     2.00   0.045      .036447    3.292467
--------------------+----------------------------------------------------------------
           /lnsig2u |  -2.918486   1.568492                     -5.992673    .1557023
--------------------+----------------------------------------------------------------
            sigma_u |   .2324122   .1822683                      .0499698    1.080962
                rho |   .0512473   .0762616                      .0024908    .5388471
-------------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     0.50 Prob >= chibar2 = 0.240

. 
. 
. ** Non-parametric Tests
. 
. use all_sessions_full, clear

. keep if type == 0
(512 observations deleted)

. 
. collapse total_info, by(treatment session)

. 
. gen treat1 = 0

. replace treat1 = 1 if treatment == 1
(4 real changes made)

. 
. gen treat2 = 0

. replace treat2 = 1 if treatment == 2
(4 real changes made)

. 
. gen treat3 = 0

. replace treat3 = 1 if treatment == 3
(4 real changes made)

. 
. gen treat4 = 0

. replace treat4 = 1 if treatment == 4
(4 real changes made)

. 
. 
. ranksum total_info, by(treat1)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat1 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          97         102
           1 |        4          39          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat1==0) = total_~o(treat1==1)
             z =  -0.607
    Prob > |z| =   0.5440

. ranksum total_info, by(treat2)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat2 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          95         102
           1 |        4          41          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat2==0) = total_~o(treat2==1)
             z =  -0.849
    Prob > |z| =   0.3956

. ranksum total_info, by(treat3)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat3 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          97         102
           1 |        4          39          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat3==0) = total_~o(treat3==1)
             z =  -0.607
    Prob > |z| =   0.5440

. ranksum total_info, by(treat4)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat4 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12         119         102
           1 |        4          17          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat4==0) = total_~o(treat4==1)
             z =   2.063
    Prob > |z| =   0.0391

. 
. use all_sessions_full, clear

. keep if type == 0
(512 observations deleted)

. 
. collapse total_info if endowment == 500, by(treatment session)

. 
. gen treat1 = 0

. replace treat1 = 1 if treatment == 1
(4 real changes made)

. 
. gen treat2 = 0

. replace treat2 = 1 if treatment == 2
(4 real changes made)

. 
. gen treat3 = 0

. replace treat3 = 1 if treatment == 3
(4 real changes made)

. 
. gen treat4 = 0

. replace treat4 = 1 if treatment == 4
(4 real changes made)

. 
. ranksum total_info, by(treat1)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat1 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          94         102
           1 |        4          42          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat1==0) = total_~o(treat1==1)
             z =  -0.971
    Prob > |z| =   0.3316

. ranksum total_info, by(treat2)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat2 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          91         102
           1 |        4          45          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat2==0) = total_~o(treat2==1)
             z =  -1.335
    Prob > |z| =   0.1819

. ranksum total_info, by(treat3)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat3 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12         118         102
           1 |        4          18          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat3==0) = total_~o(treat3==1)
             z =   1.942
    Prob > |z| =   0.0522

. ranksum total_info, by(treat4)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat4 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12         105         102
           1 |        4          31          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat4==0) = total_~o(treat4==1)
             z =   0.364
    Prob > |z| =   0.7158

. 
. use all_sessions_full, clear

. keep if type == 0
(512 observations deleted)

. 
. collapse total_info if endowment == 100, by(treatment session)

. 
. gen treat1 = 0

. replace treat1 = 1 if treatment == 1
(4 real changes made)

. 
. gen treat2 = 0

. replace treat2 = 1 if treatment == 2
(4 real changes made)

. 
. gen treat3 = 0

. replace treat3 = 1 if treatment == 3
(4 real changes made)

. 
. gen treat4 = 0

. replace treat4 = 1 if treatment == 4
(4 real changes made)

. 
. ranksum total_info, by(treat1)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat1 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12        99.5         102
           1 |        4        36.5          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat1==0) = total_~o(treat1==1)
             z =  -0.303
    Prob > |z| =   0.7616

. ranksum total_info, by(treat2)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat2 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12       100.5         102
           1 |        4        35.5          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat2==0) = total_~o(treat2==1)
             z =  -0.182
    Prob > |z| =   0.8556

. ranksum total_info, by(treat3)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat3 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12          90         102
           1 |        4          46          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat3==0) = total_~o(treat3==1)
             z =  -1.456
    Prob > |z| =   0.1453

. ranksum total_info, by(treat4)

Two-sample Wilcoxon rank-sum (Mann-Whitney) test

      treat4 |      obs    rank sum    expected
-------------+---------------------------------
           0 |       12         118         102
           1 |        4          18          34
-------------+---------------------------------
    combined |       16         136         136

unadjusted variance       68.00
adjustment for ties       -0.10
                     ----------
adjusted variance         67.90

Ho: total_~o(treat4==0) = total_~o(treat4==1)
             z =   1.942
    Prob > |z| =   0.0522

. 
. use all_sessions_full, clear

. keep if type == 0
(512 observations deleted)

. 
. 
. gen conflict=1  if IncumbentAdvantage<0 &  dist_tax>0
(3705 missing values generated)

. replace conflict=2 if IncumbentAdvantage>0 &  dist_tax<0
(1390 real changes made)

. replace conflict=3 if IncumbentAdvantage<0 &  dist_tax<0
(1320 real changes made)

. replace conflict=4 if IncumbentAdvantage>0 &  dist_tax>0
(135 real changes made)

. 
. label define conflict 1 "Negative Own vs. Positive National"

. label define conflict 2 "Positive Own vs. Negative National", add

. label define conflict 3 "Negative Own and Negative National", add

. label define conflict 4 "Positive Own and Positive National", add

. label values conflict conflict

. 
. collapse VoteInc approve if conflict!=., by(election  session conflict info_nat)

. 
. gen Vote_Incumbent_No_info = VoteIncumbent if election==1 & info==0
(121 missing values generated)

. gen Vote_Incumbent_info = VoteIncumbent[_n+1] if election==1 & info==0
(121 missing values generated)

. 
. gen Approve_Incumbent_No_info = approve if election==0 & info==0
(118 missing values generated)

. gen Approve_Incumbent_info = approve[_n+1] if election==0 & info==0
(118 missing values generated)

. 
. signrank  Vote_Incumbent_info=Vote_Incumbent_No_info if conflict==1

Wilcoxon signed-rank test

        sign |      obs   sum ranks    expected
-------------+---------------------------------
    positive |        2           5           3
    negative |        1           1           3
        zero |        0           0           0
-------------+---------------------------------
         all |        3           6           6

unadjusted variance        3.50
adjustment for ties        0.00
adjustment for zeros       0.00
                     ----------
adjusted variance          3.50

Ho: Vote_Incumbent_info = Vote_Incumbent_No_info 
             z =   1.069
    Prob > |z| =   0.2850

. signrank  Vote_Incumbent_info=Vote_Incumbent_No_info if conflict==2

Wilcoxon signed-rank test

        sign |      obs   sum ranks    expected
-------------+---------------------------------
    positive |        7          46        67.5
    negative |        8          89        67.5
        zero |        1           1           1
-------------+---------------------------------
         all |       16         136         136

unadjusted variance      374.00
adjustment for ties       -0.13
adjustment for zeros      -0.25
                     ----------
adjusted variance        373.63

Ho: Vote_Incumbent_info = Vote_Incumbent_No_info 
             z =  -1.112
    Prob > |z| =   0.2660

. 
. signrank  Approve_Incumbent_No_info= Approve_Incumbent_info if conflict==1

Wilcoxon signed-rank test

        sign |      obs   sum ranks    expected
-------------+---------------------------------
    positive |        0           0         7.5
    negative |        5          15         7.5
        zero |        0           0           0
-------------+---------------------------------
         all |        5          15          15

unadjusted variance       13.75
adjustment for ties        0.00
adjustment for zeros       0.00
                     ----------
adjusted variance         13.75

Ho: Approve_Incumbent_No_info = Approve_Incumbent_info 
             z =  -2.023
    Prob > |z| =   0.0431

. signrank  Approve_Incumbent_No_info= Approve_Incumbent_info if conflict==2

Wilcoxon signed-rank test

        sign |      obs   sum ranks    expected
-------------+---------------------------------
    positive |        9          98          68
    negative |        7          38          68
        zero |        0           0           0
-------------+---------------------------------
         all |       16         136         136

unadjusted variance      374.00
adjustment for ties        0.00
adjustment for zeros       0.00
                     ----------
adjusted variance        374.00

Ho: Approve_Incumbent_No_info = Approve_Incumbent_info 
             z =   1.551
    Prob > |z| =   0.1208

. 
. 
. log close       
      name:  <unnamed>
       log:  C:\Users\jdr08_000\Documents\Information_And_Economic_Voting.log
  log type:  text
 closed on:  10 May 2016, 14:47:54
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